Anomaly detection refers to identification of items, events or observations, which do not conform to an expected pattern or other items in a dataset. Typically, anomalous items may indicate a problem. As an example, anomalous items in a medical test results may indicate medical problems.
Anomaly detection may be applicable in a variety of domains, such as intrusion detection for cyber-security, fraud detection for credit cards, fault detection in safety critical systems, health system monitoring, event detection in sensor networks, detecting Eco-system disturbances, or the like.